U.S. patent application number 11/656315 was filed with the patent office on 2007-07-26 for collagen density and structural change measurement and mapping in tissue.
Invention is credited to Everette C. Burdette, Scott P. Huntley.
Application Number | 20070173720 11/656315 |
Document ID | / |
Family ID | 38286410 |
Filed Date | 2007-07-26 |
United States Patent
Application |
20070173720 |
Kind Code |
A1 |
Burdette; Everette C. ; et
al. |
July 26, 2007 |
Collagen density and structural change measurement and mapping in
tissue
Abstract
A method and system for two and three dimensional mapping of
tissue density and/or structural changes from image data and/or
spatial reflected or transmitted signal maps, and correlating the
maps to changes in collagen density. The method and system includes
the steps of: receiving an image or spatial maps of
acoustic-derived RF signal data from tissue comprised of multiple
pixels, segregating the image into groups of pixels, each group of
pixels having characteristics within a defined class, establishing
a baseline set of classes corresponding to initial conditions of
the imaged/mapped tissue, measuring a differential in the set of
classes for a group of pixels, the differential corresponding to a
change in pixel values for the group of pixels, correlating said
measured differential to a density change for the tissue
corresponding to the group of pixels, and overlaying an indication
of collagen density over the tissue image or mapped signal
responses correlated with thermal dose indicating a change in
collagen density for the tissue.
Inventors: |
Burdette; Everette C.;
(Champaign, IL) ; Huntley; Scott P.; (Danville,
CA) |
Correspondence
Address: |
FOLEY & LARDNER LLP
321 NORTH CLARK STREET
SUITE 2800
CHICAGO
IL
60610-4764
US
|
Family ID: |
38286410 |
Appl. No.: |
11/656315 |
Filed: |
January 19, 2007 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60760220 |
Jan 19, 2006 |
|
|
|
Current U.S.
Class: |
600/438 ;
600/437 |
Current CPC
Class: |
G06T 2207/10132
20130101; G01S 7/52071 20130101; G06T 2207/30024 20130101; A61B
8/08 20130101; G06T 7/0012 20130101 |
Class at
Publication: |
600/438 ;
600/437 |
International
Class: |
A61B 8/00 20060101
A61B008/00 |
Claims
1. A system for measuring collagen structural changes responsive to
collagen treatment, comprising: a source for producing ultrasound
energy to probe collagen containing tissue which has undergone a
change from treatment; a detector for receiving an acoustic signal
from the collagen containing tissue; a memory unit; a data analysis
system for operating on the acoustic signal for assigning a value
to a pixel of a plane in the collagen containing tissue, such value
to be based on acoustic characteristics derived from acoustic
backscattered signal from that two dimensional region of a plane in
the collagen containing tissue; the data analysis system using the
changes in the acoustic value of at least one pixel to provide a
qualitative metric of the change in collagen containing tissue
properties within the collagen containing tissue as represented by
the at least one pixel.
2. The system as defined in claim 1 wherein the data analysis
system includes computer software executed by a computer to define
a region of interest in said image of the collagen containing
tissue and segregates said region of interest into groups of at
least one pixel.
3. The system as defined in claim 1 wherein the data analysis
system includes computer software executed by a computer to assign
color values to at least one pixel corresponding to differing
changes in properties in the collagen containing tissue represented
by at least one pixel.
4. The system as defined in claim 1 wherein at lease one pixel
comprises a voxel.
5. The system as defined in claim 1 further including a collagen
treatment device.
6. The system as defined in claim 5 wherein the collagen treatment
device comprises at least one of a microwave unit, a laser unit, an
RF unit, an electrocautery unit, a thermal unit, and an ultrasound
unit.
7. The system as defined in claim 1 further including computer
software executable by the data analysis system for analyzing the
acoustic signal.
8. The system as defined in claim 4 wherein the data analysis
system assigns color values to the voxel corresponding to differing
changes in the collagen containing tissue properties in the tissue
region represented by the voxel; and generating an overlay data to
display said color-coded voxel over a standard acoustic image.
Description
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS
[0001] This application claims the benefit under 35 USC 119(e) of
U.S. Provisional Application No. 60/760,220, filed Jan. 19, 2006,
incorporated herein by reference in its entirety.
FIELD OF THE INVENTION
[0002] This invention relates to tissue monitoring and mapping
equipment and methods, and more particularly, to methods and
systems for monitoring and mapping changes in the collagen content
and/or structures in tissue.
BACKGROUND OF INVENTION
[0003] Collagen is the major insoluble fibrous protein in the
extracellular matrix and in connective tissue. There are at least
nineteen types of collagen, but 80% to 90% of the collagen in the
body is composed of the conventional well-known Type I, Type II,
and Type III forms. The collagen molecule is a triple helix, each
helical coil a biological polypeptide polymer constructed from
glycine (C.sub.2H.sub.5NO.sub.2), alanine (C.sub.3H.sub.7NO.sub.2),
proline (C.sub.5H.sub.9NO.sub.2), and hydroproline
(C.sub.5H.sub.9NO.sub.3). As the three helices wrap around each
other, hydrogen bonds form between each helix to maintain the
structure. Collagen molecules pack together to form long, thin
fibrils. The most prominent collagen types are:
Type I. The primary component of tendons, ligaments, and bones.
Type II. The primary protein constituent (more than 50%) in
cartilage.
Type III. Strengthens the walls of hollow structures like arteries,
the intestine, and the uterus.
Type IV. Forms the basal lamina (also called the basement membrane)
of epithelia.
[0004] As a support structure, collagen fibrils are found in many
environments within the body. The strength and relative elasticity
of the collagen structure allow tendon and ligament structures to
function in their role which requires great strength to manipulate
skeletal structures. Up to 90% of the dry weight of tendons is
collagen (at least 30% of the total weight), up to 50% of the dry
weight of articular cartilage and synovial tissue is collagen (5%
to 30% of total weight). Collagen comprises 75% of the dry weight
of skin.
[0005] The helical structure and the nature of the hydrogen bond
cross-linking of the collagen molecule cause it to react when
heated. The cross-linking bonds break and the helix, which is a
type of spring structure, collapses somewhat. The result is a
shrinkage, not unlike the process which occurs when a woolen
garment is washed in hot water and heated in a dryer. The amount of
shrinkage is a function of time and temperature [see FIG. 1] and is
well known.
[0006] Several therapeutic remedies have been developed which
utilize the thermal response of collagen to affect shrinkage and/or
for treating disease and, thereby, therapy. Among these are
capsulorrhaphy, or the shrinkage of the tendon and capsular
properties of the joints, shrinkage of the endopelvic fascia to
address urinary incontinence, shrinkage of the bladder neck to
affect treatment for urinary incontinence, shrinkage of
sub-epidermal collagen for producing tightening of tissue to affect
cosmetic outcomes, thermal treatment of benign and malignant
tumors, among others.
[0007] A limitation of procedures for collagen shrinkage, however,
is that the cell necrosis accompanying those procedures [see FIG.
1] weakens the structural integrity of the fibrils. It is known
that shrinking capsular tissue more than 20% will weaken a
structure so much that it will distort more under normal forces
than it would if there had been no shrinkage at all [see FIG. 2].
Treatment of tumors usually involves delivering a thermal dose that
guarantees cell necrosis, thus significantly changing collagen
structure.
[0008] Thermally-induced shrinkage procedures have been received
with moderate success because they have often produced variable
results. Collagen shrinkage is a function of both time and
temperature, but relatively small variations in either time or
temperature can have dramatic results on the level of shrinkage
[see FIG. 3]. Structures experiencing overshrinkage are likely to
have limited, or adverse results. Structures with insufficient
shrinkage are likely to have limited results.
[0009] Some therapy systems measure tissue temperature during
treatment using invasive probes and predict associated tissue
modification, while others estimate the temperature based on
power-time-temperature parametric curves established from imperical
measurements. But, because thermal dose, and thus collagen
shrinkage, is an integral function of both time and temperature in
combination with spatial distribution, and since slight variations
in temperature during a specific time period can cause dramatic
changes in collagen shrinkage [see FIG. 3], temperature measurement
alone is not truly sufficient. In response to the need to
effectively determine dosage of the thermal treatment, a
noninvasive measure of the thermal dose or its affects, including
collagen changes, is badly needed.
[0010] Since optimizing collagen modification, including shrinkage,
is the goal of specific procedures, what is needed is a system and
method for directly measuring the shrinkage of the collagen
structure, rather than temperature. A system and method which could
monitor tissue properties concurrent with treatment, signaling the
operator to halt thermal application when collagen shrinkage
approaches 20% could produce greatly improved results [see FIG. 3],
reducing the inconsistency associated with the thermal shrinkage
procedures.
[0011] The limitations of the previous art for monitoring tissue
treatment resulting from thermal injury are inadequate to provide
information directly related to collagen changes sufficient to
provide optimal control of extent of collagen structural
modification, including shrinkage.
[0012] It has been demonstrated that changes in collagen content of
tissue affects certain acoustic properties, namely the speed of
sound in that tissue structure and the absorption of the acoustic
energy as it passes through that tissue [see FIG. 4A]. It has been
shown in the art that there is a linear function of both acoustic
velocity and acoustic attenuation (see FIG. 4B) with variations in
collagen content. Acoustic velocity changes 5 m/sec/(% change in
collagen concentration) and acoustic attenuation changes 0.666
db/m/(% change in collagen concentration).
[0013] As an example, a 20% shrinkage in a collagen structure
having an initial collagen content of 30% should cause a 25%
increase in the % collagen by weight of the tissue structure. Since
many collagen structures are 5% to 30% collagen (by weight), a 25%
increase in density due to therapeutic shrinkage would cause a
change in collagen content of 1.25% to 7.5%. These changes would
correspond to changes in acoustic velocity of 6.25 m/sec to 37.5
m/sec, for initial collagen contents of 5% and 30%, respectively
(see FIG. 5A). These changes would correspond to changes in
acoustic attenuation of 0.833 db/m to 5 db/m, respectively [see
FIG. 5B].
[0014] In addition to changes in acoustic velocity and attenuation,
the structural patterns of the tissue change permanently as a
function of thermally-induced necrosis and density changes. These
patterns may be characterized in an analysis of the structures in
the 2D or 3D acoustic image or in 2D spatial maps of acoustic
signals that are reflected from or transmitted through the tissue
in those locations. Applying pattern recognition methods and/or
expert system techniques to the backscatter image or signal mapping
data can yield useful information in addition to attenuation and
velocity measurements alone.
[0015] Ultrasound (acoustic) imaging has been used in medical
imaging for years to differentiate tissue structures. These imaging
techniques have examined acoustic properties of ultrasound waves as
they travel through and reflect off of tissue to distinguish tissue
types and the boundaries between those types. These devices map
tissue in two dimensions (along a plane in line with an imaging
transducer) or three dimensions (by using multi-element imaging
transducers or single-line imaging transducers whose focus or
location changes during the process. Two of the acoustic properties
used in these imaging techniques are acoustic velocity and acoustic
attenuation. Further, structural change analyses using pattern
recognition methods can provide an ability to track changes in
tissue structure/collagen structure from baseline using
backscattered image information.
[0016] The ability to map those changes in tissue and assign
changes in collagen density to the mapped functions would allow
users the ability to monitor, in real time, the therapy effect they
are seeking to accomplish.
SUMMARY OF THE INVENTION
[0017] The subject invention therefore includes a system and method
for mapping acoustic changes from an ultrasound image of tissue
induced by a structural change or thermal injury and mapping that
information in a pixilated form. That is, each pixel, or square, in
a two dimensional image or each voxel, or cube, in a three
dimensional image, will be assigned acoustic characteristics based
on the backscattered signal from that region and/or based on the
transmitted signal through a specific tissue region. In particular,
such system and method shall assign acoustic velocity values and
acoustic attenuation values to each of the pixels.
[0018] As the treatment proceeds, the system and method will assign
change values, and assign changes in collagen content concentration
to those change values, to the acoustic properties for each pixel.
The changes preferably are color-coded to make interpretation of
the changes easier for users who are not familiar with interpreting
ultrasound images.
[0019] An object of the invention is to provide an improved system
and method to assign patterns or classes to groups of pixels or
voxels for specific collagen changes based upon the backscatter
patterns in the ultrasound image. Specific types of changes in
patterns are correlated with known classes of patterns for groups
of pixels.
[0020] Another object of this invention is to provide an improved
system and method to correlate changes in the acoustic properties
directly to changes in the collagen content in tissue and use those
changes in acoustic properties to provide feedback for the
application of thermal energy during a collagen shrinkage
procedure.
[0021] Another object of this invention is to provide an improved
system and method to determine acoustic property changes
characteristic of the spatial representations of an acoustic signal
and using those assignments to create a two dimensional or three
dimensional map of the changes in collagen concentration of a
tissue structure.
[0022] Another object of this invention is to provide an improved
system and method to use color-coding when displaying the two
dimensional or three dimensional maps of changes in collagen
density.
[0023] Another object of this invention is to provide an improved
system and method to use color-coding when displaying the two
dimensional or three dimensional maps of changes in structural
patterns in groups of pixels/voxels which correspond to changes in
collagen structure and/or content.
[0024] Another object of this invention is to provide an improved
system and method to measure the structural patterns of the tissue
that are affected as a function of thermally-induced necrosis and
density changes. These patterns may be characterized in an analysis
of the structures in the acoustic image or in 2D spatial maps of
acoustic signals that are reflected from or transmitted through the
tissue in those locations. Applying pattern recognition methods to
the image or signal mapping data can yield useful information in
addition to attenuation and velocity measurements alone.
[0025] Another object of this invention is to provide an improved
system and method to cross-correlate each of the types of measured
changes in pairs or in total with each other to provide a sensitive
system and method for determining changes in tissue collagen,
including shrinkage and tissue necrosis.
[0026] Another object of this invention is to provide an improved
system and method to use the measured tissue changes to correlate
to tissue damage with changes in tissue structure and/or acoustic
property changes as a result of treatment.
[0027] Since essentially all human tissue contains collagen in the
interstitial tissue and since this invention describes measurements
of changes in collagen concentration and/or collagen structure, and
since changes in collagen concentration and structure occur in most
thermal treatments, particularly those treatments intended to
shrink collagen structures, this invention is applicable for
monitoring collagen shrinkage procedures in all tissue structures
of all types, both external and internal.
[0028] Further advantages and features of the invention will be
apparent from the following specifications, claims and drawings,
illustrating the preferred embodiments of the invention.
[0029] FIG. 1 shows thermal effects on tissue;
[0030] FIG. 2 shows strength of collagen containing tissue post
thermal remodeling;
[0031] FIG. 3 shows time/temperature influences on collagen
shrinkage;
[0032] FIG. 4A shows relative changes in acoustic velocity and FIG.
4B acoustic attenuation properties with respect to changes in the
collagen content of tissue;
[0033] FIG. 5A shows changes in acoustic velocity as a function of
initial collagen content and percentage of collagen shrinkage; and
FIG. 5B shows changes in acoustic attenuation as a function of
initial collagen content and percentage of collagen shrinkage;
[0034] FIG. 6 shows a system for monitoring and mapping of tissue
collagen shrinkage using ultrasound backscatter information and/or
measured acoustic data reflected from or transmitted through tissue
structures;
[0035] FIG. 7 shows a block diagram of one form of the tissue
mapping workstation;
[0036] FIG. 8A shows a diagram of a neural element with four inputs
for determining changes in backscatter associated with a structural
change in a small tissue region to determine the magnitude of
change for a pixel or group of pixels; and FIG. 8B shows a
preferred neural network with three inputs for each group of
pixels;
[0037] FIG. 9A shows a diagram of the surrounding pixels used to
define a set of vectors used to determine the transfer function for
a single pixel; FIG. 9B shows a diagram of groups of pixels used to
define the vectors for a transfer function for a region of interest
group made up of multiple pixels; and
[0038] FIG. 10 shows a flow diagram of a method for monitoring and
displaying on a workstation the changes in collagen/tissue
structure during a therapy procedure.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0039] The subject invention includes a system and method for
mapping acoustic changes from an ultrasound image of tissue induced
by a structural change or controlled thermal injury and mapping
that information in a pixilated form. That is, each pixel, or
square, in a two dimensional image or each voxel, or cube, in a
three dimensional image, will be assigned acoustic characteristics
based on the backscattered signal from that region and/or based on
the transmitted signal through a specific tissue region. In
particular, such a system and method assigns acoustic velocity
values and acoustic attenuation values to each of the pixels.
[0040] As the treatment proceeds, the system and method will assign
change values, and assign changes in collagen content concentration
to those change values, to the acoustic properties for each pixel.
The changes are most preferably color-coded to make interpretation
of the changes easier for users who are not familiar with
interpreting ultrasound images.
[0041] An example of a system 10 which can be used to implement the
principles of the present invention is shown in FIG. 6. The system
10 includes an ultrasound imaging device 12 to which a tissue
change mapping workstation or system 14 is connected. The
ultrasound imaging system 12 includes a computer/microprocessor 16
and a transmitter/transducer/receiver unit 18. The
transmitter/transducer/receiver unit 18 is coupled to the computer
16 through an electrical cable 20. The
transmitter/transducer/receiver unit 18 emits ultrasound energy and
receives the energy backscattered by the tissue. This information
is provided to the computer 16 which processes the backscattered
data to generate images displayed on a display screen 22. Such
ultrasound imaging systems are well known within the art. The
tissue mapping workstation 14 is shown coupled to the computer 16
for communication of image data through an electrical cable 24 or
other conventional method (wireless, e.g.).
[0042] The system 10 of the present invention can be used in
conjunction with any conventional thermal treatment device such as
a microwave, laser, RF, electrocautery, or ultrasound therapeutic
device; but the use of the system 10 is not limited to such
applications. For example, the system 10 can be used to monitor
changes in collagen or tissue structure which is responding to a
chemical, either injected into the tissue or administered
topically.
[0043] The display of image data on the screen 22 of the ultrasound
imaging device 12 is well known and can be represented in several
forms. In operation of the system 10, ultrasound energy is emitted
from the transmitted portion of transmitter/transducer unit 18
towards the tissue to be displayed. This energy is backscattered
differently by different types of tissue. This backscattered
ultrasound energy is comprised of spectral reflection and
interference reflection portions. The backscattered energy is
received by the transducers of the transmitter/transducer 18 and
converted to grayscale intensity data. The grayscale intensity data
is stored in shared memory, a video RAM or similarly disposed
within the system 10. The grayscale intensity data is retrieved
from an integral and conventional memory or video RAM and used to
generate the driving signal for the display screen 22. In another
embodiment of the invention, the ultrasound signal is transmitted
through the tissue and received by a transducer on the opposing
side. This through transmission signal is then converted to
grayscale intensity data and displayed on the display screen 22.
Most commercially available ultrasound systems provide a video data
port so the signal used to drive the display 22 may be recorded.
This port is typically a RS-170 port and the data provided through
such ports are well known. Alternatively, there are ultrasound
imaging systems that provide for digitally interfacing with an
external form of the computer 16; and both the data are received
from the ultrasound imaging system in digital form and processed
and displayed on the system 10. Such ultrasound systems 10 often
also provide for digital control of a number of the ultrasound
system operating parameters, such as field of view, video settings,
image probe selection, internal ultrasound imaging system
processing settings, and similar functions. A few ultrasound
imaging systems 10 also provide access to the raw RF data prior to
any internal processing within the ultrasound imaging system.
[0044] Preferably, the mapping workstation 14 either receives the
video data signal from the video data port and digitizes the signal
to generate pixel data or interfaces to an available digital
interface port on the ultrasound imaging system 10. Since most
conventional ultrasound systems have a RS-170 port or other video
output connector, such an implementation makes the workstation 14
compatible with most available ultrasound systems. Alternatively,
the workstation 14 can couple to the system 10 through a parallel,
serial, USB, or IEEE1394 data port to communicate pixel or
grayscale data with the system 10, as well as control the
ultrasound imaging. An example is the Terason system with an
IEEE-1394 interface. This structure has the advantage of providing
grayscale data from the system 10 prior to the data undergoing
signal processing in the system 10. The system 10 may perform
signal processing which reduces sensitivity to the information
available in the interference reflection component of the
backscattered energy. This reduction in sensitivity may affect the
accuracy of the detection of collagen or other tissue structural
changes by the workstation 14. By obtaining pixel data prior to the
ultrasound imaging system 10 processing it, the information in
either of the reflection or transmission components may contribute
to more accurate tissue mapping. Additionally, pixel data generated
by the system 10 may contain textual information that may
complicate its processing for the tissue change mapping. The
transfer of either analog or digital image data or their
equivalents for tissue change or collagen mapping is within the
scope of the principles of the present invention.
[0045] Grayscale data is a data word which defines an intensity
level for a pixel of a display. The lowest value of the grayscale
range corresponds to a low intensity or black shade pixel while the
high value of the range corresponds to the brightest intensity or
white shade pixel. The intervening values are a shade of gray,
hence the term grayscale data. Grayscale data may be displayed on a
screen capable of displaying color data. The display 22 of
ultrasound system 10 and the display 26 of the workstation 14 are
displays capable of displaying both grayscale and color images.
[0046] Preferably, the mapping workstation 14 for monitoring tissue
structural changes and/or collagen changes includes a personal
computer or the like with an Intel Pentium Duo or AMD processor or
equivalent or better processor, 533 MHz or faster FSB, 512 MB or
more of RAM and a 40 GB or larger hard drive. Digital signal
processing can be performed on workstation 14 or by a separate
digital signal processing card coupled to the system 10 through its
system bus which processes the image data from system 10 to perform
the mapping of changes to tissue structure or collagen. The image
data to be processed may be displayed on the display 26 of the
system 10. Additionally, the system 10 can include standard
input/output (I/O) devices such as a mouse or trackball for moving
a cursor about the image displayed or the display 26 and for
identifying coordinates on the image.
[0047] FIG. 7 is a block diagram of a digital signal processing
approach within the workstation 14 used to implement the tissue
mapping of the present invention. The system 10 includes a frame
grabber 30, a data buffer 32, a computer 51 including data signal
processor 34 for executing appropriate conventional computer
software, a learning set memory 36, a working memory 38, and an
overlay buffer 40. The frame grabber 30 retrieves video data from a
video data port one frame at a time and converts the analog video
data to pixel data which is stored in the data buffer 32 for
processing. Alternatively, the frame grabber 30 can receive data
from a digital interface 50 which communicates with the system 10
through a digital data port to obtain grayscale data generated by
the system 10. The grayscale data is used by the system 10 to
produce the video signal which drives display 22 and may or may not
undergo digital signal processing prior to its transfer to the
workstation 14. Typically, frame data is provided to the display 22
at a rate of approximately 9 to 30 frames a second. To attenuate
noise in the image data, several frames of data may be retrieved
and averaged for each pixel. This averaged pixel data may then be
stored in the data buffer 32 for processing by the processor 34
within the workstation computer 51.
[0048] Prior to initiation of thermal treatment, a treating
physician preferably selects a region of interest within the image
displayed on the display 26, although the entire display 26 may be
identified as the region of interest. The region may be identified
by using a pointing device 52 to outline the region of interest.
The system 10 evaluates the image data within the region of
interest during the monitoring period for mapping of tissue
changes. Preferably, the region of interest is defined by clicking
on a first and second location on the display 26 to define an upper
left and lower right corner of a rectangle or square, although
other region shapes may be used. Once the region of interest is
defined, the data signal processor 34 segregates the region of
interest into predefined groups of pixels for temperature mapping.
A group of pixels may be defined as a single pixel. Preferably, the
groups of pixels contain multiple pixels. Multiple pixel groups are
less sensitive to ultrasound probe position changes. Preferably,
the groups of pixels segregate the region of interest into an
integer number of pixel groups.
[0049] Once the region of interest and groups of pixels are
defined, the data signal processor 34 and/or the computer 51
preferably generates a neural element for each group of pixels and
builds a learning set of initial baseline values and transfer
functions for each neural element. The baseline values are stored
in the learning set memory 36. Baseline values for a group of
pixels are discussed in more detail below. The baseline values
provide information to the data signal processor 34 about the
homogeneity of a group of pixels and its surrounding neighborhood.
This baseline information may be used to detect changes caused by
thermal treatment which are correlated to temperature values and
changes.
[0050] One set of baseline values for a group of pixels may include
a differential measurement of the grayscale values within and
outside a group of pixels. For example, an average grayscale value
for a group of pixels may be computed and differential grayscale
value for each pixel bordering the pixel group may be calculated
and accumulated. Such a measurement provides an indication of the
smoothness of the image in the area of the pixel groups. Likewise,
gradients related to grayscale values at the boundaries of a pixel
group may be used to define the change in an image area prior to
initiation of thermal treatment. Other examples of baseline values
include the detection, counting, and measurement of edges in the
vicinity of a pixel group. Such edge detection and measurement may
be performed using threshold, gradient, and Canny techniques, which
are well known in the art. These techniques provide a baseline
measurement for detecting and counting of edges in the vicinity of
a pixel group, the smoothness of the image in the area of the pixel
group, the homogeneity of the area around the pixel group, the
similarity of the areas on opposing sides of the pixel group, a
measure of the amount of grayscale change in the area of the pixel
group, respectively. By using these techniques to establish
baseline values and then compute changes in these values as tissue
structural change occurs, differential values indicative of the
amount of change caused by the treatment-induced structural changes
may be discerned and quantized.
[0051] After thermal treatment begins, the data signal processor 34
uses the pixel values stored in the buffer 32 for new image frame
data to generate new transfer function elements of the image
currently being displayed. These compared to the learning data in
the learning set memory 36 to measure an image change for each
group of pixels within the region of interest. The measured image
change, typically expressed in grayscale units, is correlated to
changes in collagen and/or tissue structure for the tissue area
corresponding to the pixel group. This change is compared to
thresholds for the structural/collagen physiological change ranges
to ascertain the particular range in which the tissue resides.
Identification of a specific structural/collagen/thermal dose range
for a pixel group is then used to generate overlay image data which
is stored in the overlay buffer 40. The overlay image data is
converted to analog frame data and provided to the display 26. The
overlay image data is displayed on portions of the image on the
display 26 as a colorwash overlay to indicate degree of
collagen/structural change for tissue areas corresponding to the
groups of pixels. Alternatively, the overlay image data may remain
in digital form and an I/O controller implemented for communicating
the pixel data to the system 10. The pixel data may be stored in
the video RAM of the system 10 and used to colorwash overlay a
portion of the display 22 to indicate degrees of tissue structural
changes for each group of pixels within a region of interest.
[0052] An example neural element ("NE") is shown in FIG. 8A. The
neural element NE implements a transfer function which correlates
the input data I to an output condition O. If an actual reading of
the output condition is possible, the difference between the
correlated output condition O and the actual condition is used to
modify the transfer function so it better correlates the input data
I to a corresponding output condition O. In this way, the element
NE adjusts or learns during an ongoing process. In the present
invention, this adjustment in the neural elements permits the
system to compensate for changes in the tissue caused by local
physiological changes unassociated with changes in structural
elements. In this example, the neural element receives four inputs,
I1, I3, I5 and I7. These inputs describe the neural element and the
neural element corresponds to a pixel or group of pixels identified
by the process discussed above. The transfer function in element NE
of FIG. 8A correlates the difference between a weighted average of
the current transfer function and a baseline condition for the
transfer function contained in the learning set to a collagen
change for the pixels corresponding to the element NE. This tissue
collagen change results in activation of one of the four outputs.
The outputs indicate whether there is no change (O1), the change is
reversible (O2), the change is greater than 50% irreversible (O3),
or the change is caused by irreversible ablation (O4). Preferably,
these ranges correspond to the ones expressed in terms of
percentage change in collagen structure. The use of four
descriptors for a neural element is merely exemplary and more or
fewer descriptors may be used for each element covering different
ranges.
[0053] A preferred neural network for each group of pixels is shown
in FIG. 8B. That network shows three inputs for a set of three
transfer functions, although fewer or more may be used for a group.
The vector path transfer functions are measurements between a group
of pixels and its neighbor groups. These inputs are each provided
to four neural elements which weight them differently to compute a
weighted average. These weighted averages are each applied to the
output elements, one of each corresponds to a temperature range.
The output elements weight the applied averages and one of the
output elements is activated. Preferably, the output elements are
also provided with a thermal dose correlation factor to verify
whether the correct output element was activated. If there are any
errors, an adjustment signal is generated and supplied to the
neural elements providing the erroneous weighted average to adjust
the weighting factors W at the neural element. The states of the
output elements for each group of pixels are used to generate the
overlay colorwash image data.
[0054] The pixels which can be used to generate a transfer function
are shown in FIG. 9A. The center pixel P0 is the pixel for which a
change is to be determined. The immediately adjacent pixels P1-P8
are used to define input data I1-I8. These input values are defined
by the difference between P0 and one of the adjacent pixels. For
example, I1 is defined by the difference in the detected grayscale
between P0 and P1, I2 the difference between P0 and P2, and so on.
For groups of pixels, adjacent groups may also be utilized in the
edge detection and measurements. In FIG. 9B, pixels P9-P24 are
adjacent to the region of interest. A weighted average of all or
some of these weighted inputs may be used to define an input
function for P0. In a similar manner, this may be defined for a
group of pixels. As shown in FIG. 9B, the group of pixels denoted
by GR0 are surrounded by pixel groups GR1-GR8. In such a case, the
transfer function may be defined by the average of the difference
between each of the pixels in the top row of GR0 and the adjacent
pixels in GR1. Other transfer functions may be similarly defined
for other adjacent regions.
[0055] The input function for a group of pixels may be derived from
four or more vectors about a pixel group. The vectors, V1-V8 for a
single pixel, are shown in FIG. 9A. In FIG. 9B, the vectors may
correspond to the eight surrounding groups about the center region
GR0 or they may be defined as the single row, column and diagonal
vectors extending from the center pixel of GR0. The important
aspect of selecting a set of vectors is to define neighboring
pixels in groups which provide information about the area about a
pixel group so changes may be detected as they approach a pixel
group or as they emanate from a pixel group.
[0056] The method of the present invention may be expressed in a
flow chart as shown in FIG. 10. The treating physician preferably
begins by selecting the region of interest (Step 1). The gain of
the ultrasound system is adjusted until the number of pixels at the
lower intensity levels dominate the region of interest. In that
way, the displayed image is predominated by intensity levels which
permit the pixels to change to the higher end of the grayscale
which in turn makes a greater dynamic range of tissue structural
change mapping possible.
[0057] The region of interest is then segregated into groups of
pixels (Step 2). After groups of pixels are defined, a set of
vectors is selected for each pixel group and a transfer function
which best maps the selected set of vectors to the detected normal
homeostasis is selected (Step 3). The vectors may be differential
edge detection or gradients. Baseline values are determined and
placed in the learning memory associated with the neural element
(Step 4). The mapping workstation 14 is then ready and tissue
treatment may begin. This indication may be generated by displaying
a message on the display 26, or by some other indicator.
[0058] During treatment, image data from the system 10 is captured
and stored in the buffer 32. The vectors for each neural element
are updated and input to the neural elements (Step 5). The neural
elements compute a current transfer value and measure the
differential between the current element value and the baseline or
initial value (Step 6). The current value is stored in the memory.
Preferably, the thermal dose for the tissue in which a temperature
probe is implanted is determined and the differential change in
thermal dose is measured. This change is correlated to the change
in tissue/collagen structure and to the change in grayscale value
between the initial set of transfer function descriptors for the
corresponding neural element and the current value (Step 7). If
this grayscale unit to thermal dose correlation factor is
approximately the same as the one being used by the neural
elements, the process continues. Otherwise, the correlation or
weighting factors for the transfer functions of the neural elements
are modified.
[0059] Using the thermal dose correlation factor, each neural
element computes a structural change corresponding to the grayscale
differential between the initial value and the current value (Step
8). The differential is added to the measured initial value to
determine the degree of change for the tissue. If this change is
greater than one of the threshold doses for the thermal treatment
ranges (Step 9), the information corresponding to the detected
structural change is generated, stored in the overlay image buffer
40, and displayed as an overlay onto the image on the display 26.
The overlay data is colorized or colorwashed to display a change
indicative of the amount of thermally-induced structural change for
a feature corresponding to a group of pixels.
[0060] The system 10 described can also use one or more temperature
probes to confirm the grayscale-to-collagen change correlation
factor. In an alternative embodiment, no temperature probes are
used. Instead, the physician directs the treating device at a
tissue region being imaged and delivers a short burst of treating
radiation. The power of this radiation and its duration is provided
to the mapping system which uses this information with a tissue
energy absorption factor to calculate a power deposition for the
tissue. The power deposition corresponds to a known thermal dose
for the type of tissue identified for the feature. This change from
baseline is correlated to the grayscale differential measured for
the same region during the test pulse. This is done two or three
times to confirm or calculate an average correlation factor for the
region. A corresponding correlation factor for other tissue types
may be extrapolated from that data using known methods. Yet another
alternative embodiment to determine the correlation factor is to
match multiple levels of histologically determined tissue changes
with the changes in backscatter affecting the transfer function of
the neural elements. Once the correlation factor is calibrated in
this manner, use of the system proceeds as described above except
the steps related to using the temperature measured by the probe to
adjust the system are not performed. Yet another alternative
embodiment would utilize unprocessed front-end data from the
ultrasound system 10 by monitoring either the reflected signal or
the transmitted signal through the target tissue. Measured changes
in the reflected and/or transmitted signal would then be correlated
with multiple levels of histologically determined tissue changes
and/or with different levels of delivered thermal dose.
[0061] Additionally, the expert part of the system 10 of the
present invention can verify that the grayscale differential is
therapeutically induced and not caused by signal noise, thus
applying pattern recognition. To verify the differential, the
expert system can use edge detection techniques on the histogram
data stored for a neural element to determine whether the gradient
established by prior transfer function values confirms the shift in
histological/structural/dose range. Additionally, differences
between a current transfer function value for one neural element
and the current value for its neighboring neural elements can also
be evaluated using edge detection or imaging enhancement techniques
to confirm whether the area in the vicinity of the neural element
is approaching or at an greater level of structural change.
Additionally, or alternatively, the histogram data can be processed
using filtering or other noise alternating techniques to determine
whether the current descriptor set accurately defines a tissue or
image change. Thus, the histogram image data for each neural
element and the descriptor set values for neighboring neural
elements can be used to confirm the collagen/structural change for
a region.
[0062] In use, the treating clinician prepares a patient for
thermal treatment of a targeted tissue area. After the mapping
workstation or the mapping system 14 has established baseline
values for the transfer function for each neural element, the
mapping system 14 signals the clinician that treatment may begin.
The treating clinician then inserts or applies the treating
probe/device to a patient by a selected method and directs the
emitted energy towards the target area. As the emitted energy is
absorbed in the target area, the mapping system 14 periodically
captures pixel data. The captured data is used to update the
transfer function values which are compared to the baseline values
to generate a grayscale differential. The update rate depends upon
the digital signal processor used and the speed and amount of
memory. In a preferred embodiment, the Integral Technologies video
capture card updates video data at a rate of 15-30 frames/second.
The grayscale differential is correlated to a tissue
collagen/structural change by using a grayscale-to-temperature
correlation factor. The corresponding change determined for the
tissue corresponding to the neural element is compared to the
measurement change threshold for the treatment ranges. In an
alternative embodiment of the invention, unprocessed front-end data
from the ultrasound system 10 is monitored from either the
reflected signal or the transmitted signal through the target
tissue. Measured changes in the reflected and/or transmitted signal
would then be correlated with multiple levels of histologically
determined tissue changes and/or with different levels of delivered
thermal dose and this result mapped onto the display over the
number of pixels interrogated. If the differential for a pixel
value indicates that the structural state of the tissue has shifted
to another zone, the mapping system 14 can confirm the change
degree zone shift by using edge detection techniques on the
histogram data for the neural element or by using edge detection
techniques on the vector set values for the neural elements
adjacent to the neural element under investigation. Preferably, the
mapping system 14 reads one or more temperature probes implanted in
the tissue to confirm the grayscale-to-thermal dose correlation
factor used by the neural elements. When a range shift is detected
for the tissue corresponding to a neural element, the mapping
system 14 stores color overlay data in the overlay buffer 40 which
is transmitted to the video RAM 22 to modify the display 26. As the
treating physician observes the addition of color to the displayed
image, the probe may be relocated or the energy being supplied to
the target area adjusted. Once the treating physician is satisfied
that the target area tissue has been appropriately treated, the
treatment may cease and the treating probe removed. If the treating
physician desires to continue monitoring of the area, the
transmitter/transducer unit 18 is used to continue the generation
of image data which is compared to the baseline by the expert
system to indicate degree of collagen/structural change in the
tissue. In another embodiment of the invention, the system may
establish a predetermined limit for tissue modifications and
automatically cease treatment when the stipulated limit is
achieved.
[0063] While the present invention has been illustrated by a
description of preferred and alternative embodiments and processes,
and while the preferred and alternative embodiments and processes
have been described in considerable detail, it is not the intention
of the applicants to restrict or in any way limit the scope of the
appended claims to such detail. Additional advantages and
modifications will readily appear to those skilled in the art. For
example, the change in the backscattered data may be detected in
the signals received by the transmitter/transducer unit 18. As a
result, the signals generated by the transducers in the unit 18 may
be processed by a system built in accordance with the principles of
the present invention to determine changes in collagen or tissue
structure. Such a system is within the scope of the present
invention. Likewise while the invention has been described with
reference to images generated by ultrasound energy, the system and
method of the present invention may also be used with image data
generated from other electromagnetic imaging/detection modalities,
such as microwave reflection/transmission detection systems,
radiographic imaging methods, and other methods for tomographic
transmission measurements of ultrasound, light, microwaves,
radiographic, or other imaging energy sources. An example of an
electromagnetic system would be an array of small microwave
apertures placed adjacent to the target tissues on one or both
sides of the body region containing the target tissues. The antenna
device apertures can be simultaneously or independently excited in
either a continuous mode or a pulsed mode. Either or both the
reflected and transmitted signals may be monitored and processed in
a manner described in this invention description. Similarly,
tomographic radiographic data taken either continuously or at
intervals during a treatment may be processed with this invention
to yield tissue structural change information during therapy. These
are examples only and other imaging methods may be similarly used
and processed.
* * * * *